This disclosure relates to the field of estimating physical properties of rock formations using images of samples of the formations. More specifically, the disclosure relates to the use of images of the rock mineral grain portion of the sample, rather than the void space, to estimate one or more physical properties of the rock formation.
Mechanical response to depletion, which comprises irrecoverable volumetric strain as well as elastic deformation, strongly depends on in situ conditions and on the nature of the corresponding perturbation in terms of stress path, strain rate, fluid substitution, etc. The ability to forecast this behavior, whether for pressure support or subsidence risk assessment, hinges on our understanding of deformation mechanisms at the scale of the aggregate, their interplay with preexisting heterogeneities and their manifestation at the scale of the reservoir.
Modeling of mechanical properties traditionally relies on microstructural parameters such as porosity, mineralogy, coordination number, cemented contact area, grain size and shape, which are combined to account for trends obtained in laboratory measurements. The now widespread availability of 3D pore scale imaging techniques allows one to access the intimate make-up of a rock, offering in principle a means to fully quantify and validate the parameters used for pore-scale modeling. It also provides an opportunity to identify which of these parameters control resulting behavior, whether redundancies exist from a physical point of view, and whether they can even be measured in a meaningful way. The option of performing direct numerical simulations based on pore scale images is being increasingly utilized to complement costly laboratory measurements. See, for example, Fredrich, J. T., D. L. Lakshtanov, N. M. Lane, E. B. Liu, C. S. Natarajan, D. M. Ni, and J. J. Toms, 2014, Digital Rocks: Developing an emerging technology through to a proven capability deployed in the business. Proceedings of the Society of Petroleum Engineers Annual Technical Conference and Exhibition, Amsterdam, The Netherlands, 27-29 October.
However, an understanding of the key controls of the observed behavior remains essential for generalizations to be made.
Several approaches to compaction modeling exist depending on the application. In basin modeling and pore pressure prediction, empirical relations of exponential and power law types are often used as porosity predictors. In soil mechanics, the Cam-clay model relates the logarithm of applied pressure to the void ratio to describe both elastic and permanent deformation. For cohesive siliciclastic aggregates, yet other approaches have been proposed that use fracture mechanics to establish the conditions for grain crushing and/or pore collapse to occur. In the case of a porous sandstone as observed from a laboratory test perspective, an objective of an image-based technique would be the ability to predict an arbitrary stress path. Such prediction may use the pre-yield elastic behavior, the conditions for the onset of grain crushing and maximum rate of inelastic compaction. Such results could then be input into well-known geomechanical models for reservoir behavior forecasting as a result of depletion.
There continues to be a need for improved methods for interpreting images of rock formation samples to infer mechanical properties of the formations.